{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e0f2d69f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ray.rllib.models import ModelCatalog\n",
    "\n",
    "from agi.nl_holdem_env import NlHoldemEnvWithOpponent\n",
    "from agi.nl_holdem_net import NlHoldemNet\n",
    "ModelCatalog.register_custom_model('NlHoldemNet', NlHoldemNet)\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7ef3a51f",
   "metadata": {},
   "outputs": [],
   "source": [
    "conf = eval(open(\"confs/nl_holdem.py\").read().strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1feb96c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "env = NlHoldemEnvWithOpponent(\n",
    "        conf,opponent=\"nn\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "1e2afb46",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10/10 [00:00<00:00, 641.90it/s]\n"
     ]
    }
   ],
   "source": [
    "rewards = []\n",
    "for i in tqdm(range(10)):\n",
    "    obs = env.reset()\n",
    "    agid = env.our_pid\n",
    "    #rint(\"begin with\",agid)\n",
    "    d = False\n",
    "    while not d:\n",
    "        legal_moves = obs[\"legal_moves\"]\n",
    "        action_ind = np.random.choice(np.where(legal_moves)[0])\n",
    "        #print(\"now\",env.my_agent())\n",
    "        assert(agid == env.my_agent())\n",
    "        obs,r,d,i = env.step(action_ind)\n",
    "    rewards.append(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "a0e3bcbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.1"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.average(rewards)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "ab04906e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_observation(obs):\n",
    "    card_info = obs[\"card_info\"]\n",
    "    plt.figure(figsize=(10,2.5))\n",
    "    for i in range(6):\n",
    "        plt.subplot(2,3,i + 1)\n",
    "        plt.imshow(card_info[:,:,i],vmin=0, vmax=1)\n",
    "        \n",
    "    action_info = obs[\"action_info\"]\n",
    "    plt.figure(figsize=(10,7))\n",
    "    for i in range(25):\n",
    "        plt.subplot(5,6,i + 1)\n",
    "        plt.imshow(action_info[:,:,i],vmin=0, vmax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "ad92941f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_observation(obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "132cb088",
   "metadata": {},
   "source": [
    "## see how the env works"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "7f6a286c",
   "metadata": {},
   "outputs": [],
   "source": [
    "obs = env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "a253c777",
   "metadata": {},
   "outputs": [],
   "source": [
    "obs,r,d,i = env.step(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "113b5e19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "3e1295a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.our_pid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "31e77339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_observation(obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c9c97fd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9301d3d7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
